{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NO_</th>\n",
       "      <th>FIRST_NAME</th>\n",
       "      <th>FAMILY_NAME</th>\n",
       "      <th>NATIONAL_NO</th>\n",
       "      <th>PRODUCT_CODE</th>\n",
       "      <th>PRODUCT_NAME</th>\n",
       "      <th>MSISDN</th>\n",
       "      <th>SIMCARD_TYPE</th>\n",
       "      <th>CITY</th>\n",
       "      <th>PRICE_UNIT</th>\n",
       "      <th>...</th>\n",
       "      <th>First_ICCID</th>\n",
       "      <th>Customer_Type</th>\n",
       "      <th>Customer_Segment</th>\n",
       "      <th>Company_Name</th>\n",
       "      <th>Province</th>\n",
       "      <th>eff_date</th>\n",
       "      <th>eff_time</th>\n",
       "      <th>PAYMENT_METHOD_NAME</th>\n",
       "      <th>BANK_NAME</th>\n",
       "      <th>AU</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13792</td>\n",
       "      <td>(RTL-D-792) Data Sim 30 Days Usage Package(2.5...</td>\n",
       "      <td>9218072315</td>\n",
       "      <td>Data</td>\n",
       "      <td>تعریف نشده</td>\n",
       "      <td>120000</td>\n",
       "      <td>...</td>\n",
       "      <td>89982011441100270913</td>\n",
       "      <td>حقیقی</td>\n",
       "      <td>حقيقي</td>\n",
       "      <td>Mashhad</td>\n",
       "      <td>تهران</td>\n",
       "      <td>20170903</td>\n",
       "      <td>10:38:30</td>\n",
       "      <td>BANK GW</td>\n",
       "      <td>mellat</td>\n",
       "      <td>1.272722e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13792</td>\n",
       "      <td>(RTL-D-792) Data Sim 30 Days Usage Package(2.5...</td>\n",
       "      <td>9218072352</td>\n",
       "      <td>Data</td>\n",
       "      <td>تهران</td>\n",
       "      <td>120000</td>\n",
       "      <td>...</td>\n",
       "      <td>89982011441100271184</td>\n",
       "      <td>حقیقی</td>\n",
       "      <td>حقيقي</td>\n",
       "      <td>Mashhad</td>\n",
       "      <td>تهران</td>\n",
       "      <td>20170903</td>\n",
       "      <td>18:17:21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12640</td>\n",
       "      <td>(RTL-O-640) 3 GB pro internet 30 days</td>\n",
       "      <td>9203098713</td>\n",
       "      <td>Postpaid</td>\n",
       "      <td>کرج</td>\n",
       "      <td>135000</td>\n",
       "      <td>...</td>\n",
       "      <td>89982011441100063797</td>\n",
       "      <td>حقیقی</td>\n",
       "      <td>حقيقي</td>\n",
       "      <td>RighTel</td>\n",
       "      <td>البرز</td>\n",
       "      <td>20170903</td>\n",
       "      <td>17:34:02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14386</td>\n",
       "      <td>(RTL-A-386) Birthday  Internet(200M)</td>\n",
       "      <td>9203084311</td>\n",
       "      <td>Postpaid</td>\n",
       "      <td>تهران</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>89982011441100122015</td>\n",
       "      <td>حقیقی</td>\n",
       "      <td>حقيقي</td>\n",
       "      <td>RighTel</td>\n",
       "      <td>تهران</td>\n",
       "      <td>20170903</td>\n",
       "      <td>08:08:12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11482</td>\n",
       "      <td>(RTL-R-482)Prepaid Sim 3+3 GB Pro Internet Pac...</td>\n",
       "      <td>9213343537</td>\n",
       "      <td>Prepaid</td>\n",
       "      <td>کرج</td>\n",
       "      <td>150000</td>\n",
       "      <td>...</td>\n",
       "      <td>89982011441100236336</td>\n",
       "      <td>حقیقی</td>\n",
       "      <td>حقيقي</td>\n",
       "      <td>RighTel</td>\n",
       "      <td>البرز</td>\n",
       "      <td>20170811</td>\n",
       "      <td>02:00:07</td>\n",
       "      <td>BANK GW</td>\n",
       "      <td>parsian</td>\n",
       "      <td>6.131928e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   NO_  FIRST_NAME  FAMILY_NAME  NATIONAL_NO  PRODUCT_CODE  \\\n",
       "0    1         NaN          NaN          NaN         13792   \n",
       "1    2         NaN          NaN          NaN         13792   \n",
       "2    3         NaN          NaN          NaN         12640   \n",
       "3    4         NaN          NaN          NaN         14386   \n",
       "4    5         NaN          NaN          NaN         11482   \n",
       "\n",
       "                                        PRODUCT_NAME      MSISDN SIMCARD_TYPE  \\\n",
       "0  (RTL-D-792) Data Sim 30 Days Usage Package(2.5...  9218072315         Data   \n",
       "1  (RTL-D-792) Data Sim 30 Days Usage Package(2.5...  9218072352         Data   \n",
       "2              (RTL-O-640) 3 GB pro internet 30 days  9203098713     Postpaid   \n",
       "3               (RTL-A-386) Birthday  Internet(200M)  9203084311     Postpaid   \n",
       "4  (RTL-R-482)Prepaid Sim 3+3 GB Pro Internet Pac...  9213343537      Prepaid   \n",
       "\n",
       "         CITY  PRICE_UNIT      ...                First_ICCID  Customer_Type  \\\n",
       "0  تعریف نشده      120000      ...       89982011441100270913          حقیقی   \n",
       "1       تهران      120000      ...       89982011441100271184          حقیقی   \n",
       "2         کرج      135000      ...       89982011441100063797          حقیقی   \n",
       "3       تهران           0      ...       89982011441100122015          حقیقی   \n",
       "4         کرج      150000      ...       89982011441100236336          حقیقی   \n",
       "\n",
       "   Customer_Segment Company_Name Province  eff_date  eff_time  \\\n",
       "0             حقيقي      Mashhad    تهران  20170903  10:38:30   \n",
       "1             حقيقي      Mashhad    تهران  20170903  18:17:21   \n",
       "2             حقيقي      RighTel    البرز  20170903  17:34:02   \n",
       "3             حقيقي      RighTel    تهران  20170903  08:08:12   \n",
       "4             حقيقي      RighTel    البرز  20170811  02:00:07   \n",
       "\n",
       "   PAYMENT_METHOD_NAME BANK_NAME            AU  \n",
       "0              BANK GW    mellat  1.272722e+11  \n",
       "1                  NaN       NaN           NaN  \n",
       "2                  NaN       NaN           NaN  \n",
       "3                  NaN       NaN           NaN  \n",
       "4              BANK GW   parsian  6.131928e+08  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_table('data/Subscriber_Buy_Packages_20170903.csv',sep=',')\n",
    "data.head()  ## 一天的数据，大概13W条数据 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.数据空值，异常值，重复值处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NO_</th>\n",
       "      <th>FIRST_NAME</th>\n",
       "      <th>FAMILY_NAME</th>\n",
       "      <th>NATIONAL_NO</th>\n",
       "      <th>PRODUCT_CODE</th>\n",
       "      <th>MSISDN</th>\n",
       "      <th>PRICE_UNIT</th>\n",
       "      <th>TAX</th>\n",
       "      <th>TOTAL_PRICE</th>\n",
       "      <th>PAYMENT_DATE</th>\n",
       "      <th>SUBS_ORDER_ID</th>\n",
       "      <th>eff_date</th>\n",
       "      <th>AU</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>123185.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>123185.000000</td>\n",
       "      <td>1.231850e+05</td>\n",
       "      <td>1.231850e+05</td>\n",
       "      <td>123185.000000</td>\n",
       "      <td>1.231850e+05</td>\n",
       "      <td>1.231850e+05</td>\n",
       "      <td>1.231850e+05</td>\n",
       "      <td>1.231850e+05</td>\n",
       "      <td>1.061000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>61593.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11943.609376</td>\n",
       "      <td>9.217687e+09</td>\n",
       "      <td>8.219531e+04</td>\n",
       "      <td>1570.065065</td>\n",
       "      <td>8.376537e+04</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>5.252235e+08</td>\n",
       "      <td>2.017081e+07</td>\n",
       "      <td>3.947815e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>35560.590792</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>988.054980</td>\n",
       "      <td>1.301661e+07</td>\n",
       "      <td>1.088976e+05</td>\n",
       "      <td>7858.065519</td>\n",
       "      <td>1.144085e+05</td>\n",
       "      <td>5.698306e-03</td>\n",
       "      <td>1.332349e+05</td>\n",
       "      <td>8.408302e+02</td>\n",
       "      <td>5.620668e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11244.000000</td>\n",
       "      <td>9.010861e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>5.249355e+08</td>\n",
       "      <td>2.015091e+07</td>\n",
       "      <td>6.131132e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>30797.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11439.000000</td>\n",
       "      <td>9.212782e+09</td>\n",
       "      <td>1.200000e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.200000e+04</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>5.251036e+08</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>4.052996e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>61593.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11568.000000</td>\n",
       "      <td>9.216035e+09</td>\n",
       "      <td>4.000000e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000e+04</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>5.252729e+08</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>4.053007e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>92389.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11693.000000</td>\n",
       "      <td>9.223577e+09</td>\n",
       "      <td>1.500000e+05</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.500000e+05</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>5.253309e+08</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>1.272695e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>123185.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14386.000000</td>\n",
       "      <td>9.909558e+09</td>\n",
       "      <td>6.176000e+06</td>\n",
       "      <td>521640.000000</td>\n",
       "      <td>6.317640e+06</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>5.253834e+08</td>\n",
       "      <td>2.017090e+07</td>\n",
       "      <td>1.272993e+11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 NO_  FIRST_NAME  FAMILY_NAME  NATIONAL_NO   PRODUCT_CODE  \\\n",
       "count  123185.000000         0.0          0.0          0.0  123185.000000   \n",
       "mean    61593.000000         NaN          NaN          NaN   11943.609376   \n",
       "std     35560.590792         NaN          NaN          NaN     988.054980   \n",
       "min         1.000000         NaN          NaN          NaN   11244.000000   \n",
       "25%     30797.000000         NaN          NaN          NaN   11439.000000   \n",
       "50%     61593.000000         NaN          NaN          NaN   11568.000000   \n",
       "75%     92389.000000         NaN          NaN          NaN   11693.000000   \n",
       "max    123185.000000         NaN          NaN          NaN   14386.000000   \n",
       "\n",
       "             MSISDN    PRICE_UNIT            TAX   TOTAL_PRICE  PAYMENT_DATE  \\\n",
       "count  1.231850e+05  1.231850e+05  123185.000000  1.231850e+05  1.231850e+05   \n",
       "mean   9.217687e+09  8.219531e+04    1570.065065  8.376537e+04  2.017090e+07   \n",
       "std    1.301661e+07  1.088976e+05    7858.065519  1.144085e+05  5.698306e-03   \n",
       "min    9.010861e+09  0.000000e+00       0.000000  0.000000e+00  2.017090e+07   \n",
       "25%    9.212782e+09  1.200000e+04       0.000000  1.200000e+04  2.017090e+07   \n",
       "50%    9.216035e+09  4.000000e+04       0.000000  4.000000e+04  2.017090e+07   \n",
       "75%    9.223577e+09  1.500000e+05       0.000000  1.500000e+05  2.017090e+07   \n",
       "max    9.909558e+09  6.176000e+06  521640.000000  6.317640e+06  2.017090e+07   \n",
       "\n",
       "       SUBS_ORDER_ID      eff_date            AU  \n",
       "count   1.231850e+05  1.231850e+05  1.061000e+04  \n",
       "mean    5.252235e+08  2.017081e+07  3.947815e+10  \n",
       "std     1.332349e+05  8.408302e+02  5.620668e+10  \n",
       "min     5.249355e+08  2.015091e+07  6.131132e+08  \n",
       "25%     5.251036e+08  2.017090e+07  4.052996e+09  \n",
       "50%     5.252729e+08  2.017090e+07  4.053007e+09  \n",
       "75%     5.253309e+08  2.017090e+07  1.272695e+11  \n",
       "max     5.253834e+08  2.017090e+07  1.272993e+11  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 结果:1. 数据的异常值，重复值在数据从Oracle导出之前都已经处理完成。2.数据的空值，是确实得不到或者没有，需要按照分析需求进行填充或者丢弃。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.分析用户最常买的20个套餐包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped = data.groupby(data['PRODUCT_NAME']).count()\n",
    "grouped.sort_values('NO_',ascending=0,inplace=True)\n",
    "grouped['NO_'].head(20).plot(kind = 'bar',alpha = 0.8,label=None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.获取当天的前30名优质客户"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped = data.groupby(data['MSISDN']).sum()\n",
    "grouped.sort_values('TOTAL_PRICE',ascending=0,inplace=True)\n",
    "grouped['TOTAL_PRICE'].head(30).plot(kind = 'bar',alpha = 0.8,label=None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.获取当天各个时间段，用户订购情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PRODUCT_NAME</th>\n",
       "      <th>PAYMENT_TIME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(RTL-D-792) Data Sim 30 Days Usage Package(2.5...</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(RTL-D-792) Data Sim 30 Days Usage Package(2.5...</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(RTL-O-640) 3 GB pro internet 30 days</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(RTL-A-386) Birthday  Internet(200M)</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(RTL-R-482)Prepaid Sim 3+3 GB Pro Internet Pac...</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        PRODUCT_NAME  PAYMENT_TIME\n",
       "0  (RTL-D-792) Data Sim 30 Days Usage Package(2.5...            10\n",
       "1  (RTL-D-792) Data Sim 30 Days Usage Package(2.5...            18\n",
       "2              (RTL-O-640) 3 GB pro internet 30 days            17\n",
       "3               (RTL-A-386) Birthday  Internet(200M)             8\n",
       "4  (RTL-R-482)Prepaid Sim 3+3 GB Pro Internet Pac...             9"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = data[['PRODUCT_NAME','PAYMENT_TIME']].copy()\n",
    "data2['PAYMENT_TIME'] = data2['PAYMENT_TIME'].str.slice(0,2)\n",
    "data2['PAYMENT_TIME'] = data2['PAYMENT_TIME'].astype('int')\n",
    "data2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped = data2.groupby(data2['PAYMENT_TIME']).count()\n",
    "#grouped.sort_values('PRODUCT_NAME',ascending=0,inplace=True)\n",
    "grouped['PRODUCT_NAME'].plot(kind = 'line',alpha = 0.8,linestyle = '-.',marker = 'o')\n",
    "#plt.plot(grouped.PAYMENT_TIME,grouped['PRODUCT_NAME'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 结果：当天大概8:00到9:00，是用户订购业务的高峰期"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.分析套餐价格和套餐订购数量之间的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped = data[data['PRICE_UNIT'] > 0].groupby('PRODUCT_NAME') # 剔除掉免费的赠送套餐包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PRODUCT_CODE</th>\n",
       "      <th>PRICE_UNIT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRODUCT_NAME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(RT-R-693) 3 GB pro internet 30 days</th>\n",
       "      <td>4686</td>\n",
       "      <td>135000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RTL-D-110)100 Farsi SMS Package</th>\n",
       "      <td>4</td>\n",
       "      <td>8000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RTL-D-112)200 Farsi-English SMS Package</th>\n",
       "      <td>1</td>\n",
       "      <td>27000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RTL-D-113)500 Farsi SMS Package</th>\n",
       "      <td>6</td>\n",
       "      <td>35000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(RTL-D-344) SPRING93 Data 15 days base internet plan (0.5 GB)</th>\n",
       "      <td>31</td>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    PRODUCT_CODE  PRICE_UNIT\n",
       "PRODUCT_NAME                                                                \n",
       "(RT-R-693) 3 GB pro internet 30 days                        4686      135000\n",
       "(RTL-D-110)100 Farsi SMS Package                               4        8000\n",
       "(RTL-D-112)200 Farsi-English SMS Package                       1       27000\n",
       "(RTL-D-113)500 Farsi SMS Package                               6       35000\n",
       "(RTL-D-344) SPRING93 Data 15 days base internet...            31       70000"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data5 = pd.merge(pd.DataFrame(grouped['PRODUCT_CODE'].count()),pd.DataFrame(grouped['PRICE_UNIT'].mean()),on='PRODUCT_NAME')\n",
    "data5.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "corr = data5.corr(method = 'kendall')\n",
    "sns.heatmap(corr)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 结果:从所有套餐层面分析，套餐价格和套餐订购数量之间的关系很小。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
